Identifying risk factors of anemia among women of reproductive age in Rwanda - a cross-sectional study using secondary data from the Rwanda Demographic and Health Survey 2014/2015

Abstract

Background Anemia among Women of Reproductive Age (WRA) continues to be among the major public health problems in many developing countries, including Rwanda, where it increased in prevalence between the 2015 and 2010 Rwanda Demographic and Health Survey (RDHS) reports. A thorough understanding of its risk factors is necessary to design better interventions. However, to the best of our knowledge, no study has been conducted in Rwanda on a nationally representative sample to assess factors associated with anemia among WRA. Accordingly, this study was conducted to address such gap. Methods A quantitative, cross-sectional study was conducted using data from the RDHS 2014-2015 report. The study population consisted of 6680 WRA who were tested for anemia during the survey. Anemia was defined as having a hemoglobin level equal to or below 10.9 g/dl for a pregnant woman, and hemoglobin level equal to or below 11.9 g/dl for a non-pregnant woman. Pearson’s chi-squared test and multiple logistic regression were conducted for bivariate and multivariable analysis, respectively. Results The prevalence of anemia among WRA was 19.2% (95% CI: 18.0 - 20.5). Four factors were found to be associated with lower odds of anemia, including being obese (OR: 0.61, 95% CI: 0.40 - 0.91), being in the rich category (OR: 0.74, 95% CI: 0.63 - 0.87), sleeping under a mosquito net (OR: 0.85, 95% CI: 0.74 - 0.98), and using hormonal contraceptives (OR: 0.61, 95% CI: 0.50 - 0.73). Five factors were associated with higher odds of anemia, including being underweight (OR: 1.39, 95% CI: 1.09 - 1.78), using an intrauterine device (OR: 1.98, 95% CI: 1.05 - 3.75), being separated or widowed (OR: 1.35, 95% CI: 1.09 - 1.67), and living in the Southern province (OR: 1.45, 95% CI: 1.11 - 1.89) or in the Eastern province (OR: 1.41, 95% CI: 1.06 - 1.88). Conclusion Anemia continues to pose public health challenges; novel public health interventions should consider geographic variations in anemia risk, seek to improve women’s economic statuses, and strengthen iron supplementation especially for Intrauterine device users. Additionally, given the association between anemia and malaria, interventions to prevent malaria should be enhanced.

Urban -Rural Differential in the Association Between Household Wealth Index and Anemia Among Women in Reproductive Age in Ethiopia, 2016.

“…This finding is consistent with the findings from other studies in low and middle-income countries, which found that the associated factors of anemia among women living in the lowest wealth status were increased when compared with those living in the heights wealth status (11,18,20,22,23,33).…”

“…Multiple deficiencies tend to cluster within individuals, and the synergistic effect of these deficiencies is important in the development of anemia in rural residency (39,42,45,46). Other than residency and socioeconomic status, women who were not used hormonal contraceptive, younger age category, and no education and married were potential predictors of anemia among the studied participants in Ethiopia; other studies have reported a similar relation (4,9,10,18,23,24,33,46).…”

“…The main anemia associated variable of interest was the household wealth index and women's place of residence. Based on existing literature, other independent variables included in the analysis are described in Table 1 (4,10,18,20,22,23,33).…”

“…Besides these immediate risk factors of anemia, there are ranges of known distal factors that operate at the household and community levels. These include maternal age (4), education status (13), marital status, occupation (19), rural/urban residence (20), household wealth index (18,21), hormonal contraceptive user, and body mass index (10,22,23).…”

Differential effects of socio-demographic factors on maternal haemoglobin concentration in three sub-Saharan African Countries

“…A study in Dhaka showed a strong relationship between maternal age, education level, income level, and maternal Hb concentration [18]. Moreover, higher BMI, primiparity, and living in better-off households were associated with higher levels of Hb [21, 22]. On the contrary, low family income and large family size are negatively associated with maternal Hb concentration [24].…”